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In order to make progress in socionics, we must clearly distinguish between the three different perspectives it offers and mesh them in a triangular research program: model-ing sociological theories in the medium of multiagent technology (“sociological refer-ence”); reading sociological theories as instructions how to build innovative multiagent systems („computational reference“); and designing hybrid societies of artificial agents and human actors in accordance with social sustainabilty, democratic values and eco-nomic efficiency („praxis reference“). The issue at stake here is whether socionic re-search can help to bridge the growing gap between hardware potentials and software applications and supply the coming generation of massive parallel computing with complex „social“ networks sustained by a host of smart mini algorithms. Even though we do not have to begin from zero, and even though the borderland between sociology and DAI is no longer an unexplored terra incognita as it was a few years ago, we are still very much in the dark as to what exactly will happen when sociological models are translated into the language of DAI and as to the possible benefits or drawbacks of sociological theorizing inspired by DAI. And we still know far too little about inserting sociological theories into the inventive process of building dynamic large-scale multi-agent systems.

In order to address these issues in a way beneficial for both communities, computer science and sociology alike, we will need patience and stamina. When we break into research territory outside the confines of our well established knowledge domains, we cannot tell in advance what exactly is going to happen nor insure ourselves against possible set-backs. We cannot know at present what DAI and sociology will really learn from one another nor how they will learn it. Equally, we cannot know all the im-plications of developing an intelligent computer technology that takes social systems as its model. In spite of all the many unanswered questions, however, we may take heart for our expeditions in the socionic borderland from the precedent of classic AI.

As we know today, the famous Dartmouth Conference of 1958 which inaugurated AI research, triggered off a paradigm revolution in the computer sciences. Forty years ago, when AI was a newcomer to computer sciences, its implications were not very clear and it had to contend with opposition from traditional computer science branches.

We should keep this in mind as we strike out into a research field that not so long ago was still considered “The Unnamable”.

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